Senior/Middle Data Scientist

Kyivstar
Summary
Join Kyivstar.Tech, a Ukrainian IT company, as a Senior/Middle Data Scientist specializing in Large Language Models (LLMs). You will design and prototype data preparation pipelines for LLM training, collaborating with data engineers to scale these pipelines. Your work will directly impact model quality and capabilities by ensuring high-quality data. You will analyze large-scale data sources, develop data cleaning techniques, and monitor data quality's impact on model performance. You will also research best practices in LLM training pipelines and collaborate with cross-functional teams. This role requires strong NLP expertise, proficiency in Python and relevant libraries, and experience with deep learning frameworks. Kyivstar.Tech offers remote work options, performance bonuses, training opportunities, health and life insurance, a wellbeing program, and mobile communication reimbursement.
Requirements
- 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP
- Proven experience in data preprocessing, cleaning, and feature engineering for large-scale datasets of unstructured data (text, code, documents, etc.)
- Good knowledge of natural language processing techniques and algorithms
- Hands-on experience with modern NLP approaches including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs
- Familiarity with LLM training and fine-tuning techniques, and data requirements
- Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext)
- Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models
- Ability to write efficient, clean code and debug complex model issues
- Solid understanding of data analytics and statistics
- Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance
- Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions
- Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications
- Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML)
- Experience working in a collaborative, cross-functional environment
- Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies clearly
- Ability to rapidly prototype and iterate on ideas
Responsibilities
- Design, prototype, and validate data preparation and transformation steps for LLM training datasets, including cleaning and normalization of text, filtering of toxic content, deduplication, denoising, detection, and deletion of personal data
- Form specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher
- Analyze large-scale raw text, code, and multimodal data sources for quality, coverage, and relevance
- Develop heuristics, filtering rules, and cleaning techniques to maximize training data effectiveness
- Collaborate with data engineers to hand over prototypes for automation and scaling
- Research and develop best practices and novel techniques in LLM training pipelines
- Monitor and evaluate data quality impact on model performance through experiments and benchmarks
- Research and implement best practices in large-scale dataset creation for AI/ML models
- Document methodologies and share insights with internal teams
Preferred Qualifications
- Advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning or a related field is highly preferred
- Experience with cloud platforms (AWS, GCP or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus
Benefits
- Office or remote – it’s up to you. You can work from anywhere, and we will arrange your workplace
- Remote onboarding
- Performance bonuses for everyone (annual or quarterly — depends on the role)
- We train employees: with the opportunity to learn through the company’s library, internal resources, and programs from partners
- Health and life insurance
- Wellbeing program and corporate psychologist
- Reimbursement of expenses for Kyivstar mobile communication